


from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

_SCREAMING_SNAKE_CASE     :					int      =       TypeVar("T")
def      UpperCAmelCase__		(UpperCamelCase_							):



     """simple docstring"""






     return (position - 1) // 2
def      UpperCAmelCase__		(UpperCamelCase_							):



     """simple docstring"""






     return (2 * position) + 1
def      UpperCAmelCase__		(UpperCamelCase_							):



     """simple docstring"""






     return (2 * position) + 2

class     A__   (       Generic[T]      ):







    """simple docstring"""

    def __init__(			self       ):
         snake_case											=							[]
         snake_case											=							{}
         snake_case											=							0
    def __len__(			self       ):
         return self.elements
    def __repr__(			self       ):
         return str(self.heap       )
    def 						a_     (			self       ):
         # Check if the priority queue is empty
         return self.elements == 0
    def 						a_     (			self     ,   __snake_case     ,   __snake_case       ):
         # Add an element with given priority to the queue
         self.heap.append((elem, weight)       )
         snake_case											=							self.elements
         self.elements += 1
         self._bubble_up(__snake_case       )
    def 						a_     (			self       ):
         # Remove and return the element with lowest weight (highest priority)
         if self.elements > 1:
              self._swap_nodes(0     ,   self.elements - 1       )
         snake_case					,    snake_case											=							self.heap.pop()
         del self.position_map[elem]
         self.elements -= 1
         if self.elements > 0:
              snake_case					,    snake_case											=							self.heap[0]
              self._bubble_down(__snake_case       )
         return elem
    def 						a_     (			self     ,   __snake_case     ,   __snake_case       ):
         # Update the weight of the given key
         snake_case											=							self.position_map[elem]
         snake_case											=							(elem, weight)
         if position > 0:
              snake_case											=							get_parent_position(__snake_case       )
              snake_case					,    snake_case											=							self.heap[parent_position]
              if parent_weight > weight:
                   self._bubble_up(__snake_case       )
              else:
                   self._bubble_down(__snake_case       )
         else:
              self._bubble_down(__snake_case       )
    def 						a_     (			self     ,   __snake_case       ):
         # Place a node at the proper position (upward movement) [to be used internally
         # only]
         snake_case											=							self.position_map[elem]
         if curr_pos == 0:
              return None
         snake_case											=							get_parent_position(__snake_case       )
         snake_case					,    snake_case											=							self.heap[curr_pos]
         snake_case					,    snake_case											=							self.heap[parent_position]
         if parent_weight > weight:
              self._swap_nodes(__snake_case     ,   __snake_case       )
              return self._bubble_up(__snake_case       )
         return None
    def 						a_     (			self     ,   __snake_case       ):
         # Place a node at the proper position (downward movement) [to be used
         # internally only]
         snake_case											=							self.position_map[elem]
         snake_case					,    snake_case											=							self.heap[curr_pos]
         snake_case											=							get_child_left_position(__snake_case       )
         snake_case											=							get_child_right_position(__snake_case       )
         if child_left_position < self.elements and child_right_position < self.elements:
              snake_case					,    snake_case											=							self.heap[child_left_position]
              snake_case					,    snake_case											=							self.heap[child_right_position]
              if child_right_weight < child_left_weight and child_right_weight < weight:
                   self._swap_nodes(__snake_case     ,   __snake_case       )
                   return self._bubble_down(__snake_case       )
         if child_left_position < self.elements:
              snake_case					,    snake_case											=							self.heap[child_left_position]
              if child_left_weight < weight:
                   self._swap_nodes(__snake_case     ,   __snake_case       )
                   return self._bubble_down(__snake_case       )
         else:
              return None
         if child_right_position < self.elements:
              snake_case					,    snake_case											=							self.heap[child_right_position]
              if child_right_weight < weight:
                   self._swap_nodes(__snake_case     ,   __snake_case       )
                   return self._bubble_down(__snake_case       )
         return None




    def 						a_     (			self     ,   __snake_case     ,   __snake_case       ):
         # Swap the nodes at the given positions
         snake_case											=							self.heap[nodea_pos][0]
         snake_case											=							self.heap[nodea_pos][0]
         snake_case					,    snake_case											=							(
             self.heap[nodea_pos],
             self.heap[nodea_pos],
         )
         snake_case											=							nodea_pos
         snake_case											=							nodea_pos






class     A__   (       Generic[T]      ):







    """simple docstring"""

    def __init__(			self       ):
         snake_case											=							{}
         snake_case											=							0
    def __repr__(			self       ):
         return str(self.connections       )
    def __len__(			self       ):
         return self.nodes
    def 						a_     (			self     ,   __snake_case       ):
         # Add a node in the graph if it is not in the graph
         if node not in self.connections:
              snake_case											=							{}
              self.nodes += 1




    def 						a_     (			self     ,   __snake_case     ,   __snake_case     ,   __snake_case       ):
         # Add an edge between 2 nodes in the graph
         self.add_node(__snake_case       )
         self.add_node(__snake_case       )
         snake_case											=							weight
         snake_case											=							weight






def      UpperCAmelCase__		(UpperCamelCase_				,):



     """simple docstring"""






     snake_case											=							{node: maxsize for node in graph.connections}
     snake_case											=							{node: None for node in graph.connections}

     snake_case											=							MinPriorityQueue()
     for node, weight in dist.items():
          priority_queue.push(UpperCamelCase_				,UpperCamelCase_							)

     if priority_queue.is_empty():
          return dist, parent

     # initialization
     snake_case											=							priority_queue.extract_min()
     snake_case											=							0
     for neighbour in graph.connections[node]:
          if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
               snake_case											=							dist[node] + graph.connections[node][neighbour]
               priority_queue.update_key(UpperCamelCase_				,dist[neighbour]							)
               snake_case											=							node

    # running prim's algorithm
     while not priority_queue.is_empty():
          snake_case											=							priority_queue.extract_min()
          for neighbour in graph.connections[node]:
               if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
                    snake_case											=							dist[node] + graph.connections[node][neighbour]
                    priority_queue.update_key(UpperCamelCase_				,dist[neighbour]							)
                    snake_case											=							node
     return dist, parent








import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list

@require_torchaudio
@require_sentencepiece
class     A__   (       unittest.TestCase      ):







    """simple docstring"""

    def 						a_     (			self       ):
         snake_case											=							'''laion/clap-htsat-unfused'''
         snake_case											=							tempfile.mkdtemp()
    def 						a_     (			self     ,   **__snake_case       ):
         return RobertaTokenizer.from_pretrained(self.checkpoint     ,   **__snake_case       )
    def 						a_     (			self     ,   **__snake_case       ):
         return ClapFeatureExtractor.from_pretrained(self.checkpoint     ,   **__snake_case       )
    def 						a_     (			self       ):
         shutil.rmtree(self.tmpdirname       )
    def 						a_     (			self       ):
         snake_case											=							self.get_tokenizer()
         snake_case											=							self.get_feature_extractor()

         snake_case											=							ClapProcessor(tokenizer=__snake_case     ,   feature_extractor=__snake_case       )

         processor.save_pretrained(self.tmpdirname       )
         snake_case											=							ClapProcessor.from_pretrained(self.tmpdirname       )

         self.assertEqual(processor.tokenizer.get_vocab()     ,   tokenizer.get_vocab()       )
         self.assertIsInstance(processor.tokenizer     ,   __snake_case       )

         self.assertEqual(processor.feature_extractor.to_json_string()     ,   feature_extractor.to_json_string()       )
         self.assertIsInstance(processor.feature_extractor     ,   __snake_case       )
    def 						a_     (			self       ):
         snake_case											=							ClapProcessor(tokenizer=self.get_tokenizer()     ,   feature_extractor=self.get_feature_extractor()       )
         processor.save_pretrained(self.tmpdirname       )

         snake_case											=							self.get_tokenizer(bos_token='''(BOS)'''     ,   eos_token='''(EOS)'''       )
         snake_case											=							self.get_feature_extractor(do_normalize=__snake_case     ,   padding_value=1.0       )

         snake_case											=							ClapProcessor.from_pretrained(
             self.tmpdirname     ,   bos_token='''(BOS)'''     ,   eos_token='''(EOS)'''     ,   do_normalize=__snake_case     ,   padding_value=1.0       )

         self.assertEqual(processor.tokenizer.get_vocab()     ,   tokenizer_add_kwargs.get_vocab()       )
         self.assertIsInstance(processor.tokenizer     ,   __snake_case       )

         self.assertEqual(processor.feature_extractor.to_json_string()     ,   feature_extractor_add_kwargs.to_json_string()       )
         self.assertIsInstance(processor.feature_extractor     ,   __snake_case       )
    def 						a_     (			self       ):
         snake_case											=							self.get_feature_extractor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ClapProcessor(tokenizer=__snake_case     ,   feature_extractor=__snake_case       )

         snake_case											=							floats_list((3, 1_0_0_0)       )

         snake_case											=							feature_extractor(__snake_case     ,   return_tensors='''np'''       )
         snake_case											=							processor(audios=__snake_case     ,   return_tensors='''np'''       )

         for key in input_feat_extract.keys():
              self.assertAlmostEqual(input_feat_extract[key].sum()     ,   input_processor[key].sum()     ,   delta=1E-2       )
    def 						a_     (			self       ):
         snake_case											=							self.get_feature_extractor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ClapProcessor(tokenizer=__snake_case     ,   feature_extractor=__snake_case       )

         snake_case											=							'''This is a test string'''

         snake_case											=							processor(text=__snake_case       )

         snake_case											=							tokenizer(__snake_case       )

         for key in encoded_tok.keys():
              self.assertListEqual(encoded_tok[key]     ,   encoded_processor[key]       )
    def 						a_     (			self       ):
         snake_case											=							self.get_feature_extractor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ClapProcessor(tokenizer=__snake_case     ,   feature_extractor=__snake_case       )

         snake_case											=							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         snake_case											=							processor.batch_decode(__snake_case       )
         snake_case											=							tokenizer.batch_decode(__snake_case       )

         self.assertListEqual(__snake_case     ,   __snake_case       )




    def 						a_     (			self       ):
         snake_case											=							self.get_feature_extractor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ClapProcessor(tokenizer=__snake_case     ,   feature_extractor=__snake_case       )

         self.assertListEqual(
             processor.model_input_names[2:]     ,   feature_extractor.model_input_names     ,   msg='''`processor` and `feature_extractor` model input names do not match'''     ,   )




